Abstract #4010

Improving Ultra-High b-value Prostate Diffusion Image Reconstruction at 3T

Neha Koonjoo¹, Bo Zhu^1,2, Danyal Bhutto^1,2,3, Arnaud Guidon⁴, Matthew Christensen^1,2, Mukesh Harisinghani¹, and Matthew S Rosen^1,2,5

¹Department of Radiology, A.A Martinos Center for Biomedical Imaging / MGH, Charlestown, MA, United States, ²Harvard Medical School, Boston, MA, United States, ³Department of Biomedical Engineering, Boston University, Boston, MA, United States, ⁴GE Healthcare, Boston, MA, United States, ⁵Department of Physics, Harvard University, Cambridge, MA, United States

Synopsis

Ultra-high b-value Diffusion-weighted Prostate MR is gaining more attention in medical imaging, due to the non-invasiveness of imaging and to better contrast of malignant tissues as the lower diffusivity of water molecules can enable early diagnosis of cancer. The main drawback of MR at ultra-high b-value is the poor resultant SNR of the reconstructed images. We propose to improve the image quality of the prostate data acquired at b=2000 s/mm² using a machine learning based reconstruction approach. Significant increase in signal intensities in the central gland and peripheral zone of the prostate was observed in healthy subjects.

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